code: def __init__(self, model_name: ValidHFModel, device: Device) -> None:
      self.device = device
      # have to download the opt models in advance since they're new
      # The OPT models have a start token that we need to remove in some
      # places
      self.correction_for_start_token = 0
      accelerator = Accelerator()
      if model_name.startswith("opt-"):
          prefix = "facebook/"
          self.model = self._load_opt(prefix + model_name, device)
          self.correction_for_start_token = 1
      else:
          if model_name.startswith("gpt-neo") or model_name.startswith(
              "gpt-j"
          ):
              prefix = "EleutherAI/"
          else:
              prefix = ""
          torch.cuda.empty_cache()
          self.model = AutoModelForCausalLM.from_pretrained(
              prefix + model_name,
              max_length=1024,
              trust_remote_code=True,
              device_map="auto",
          )
      self.model = accelerator.prepare(self.model)
      self.device = accelerator.device
      # apparently the OPT models need slightly different tokenizers
      # https://huggingface.co/docs/transformers/main/en/model_doc/opt#overview
      if model_name.startswith("opt-"):
          use_fast = False
      else:
          use_fast = True
      self.tokenizer = AutoTokenizer.from_pretrained(
          prefix + model_name,
          use_fast=use_fast,
          model_max_length=1023,
      )
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Union, cast, Sequence
  from typing_extensions import Literal, get_args
  import numpy
  import torch
  import torch.nn.functional
  from transformers import AutoModelForCausalLM, AutoTokenizer
  from accelerate import Accelerator
  from .isp_dataset import ClassificationExample, Example, ExampleWithClasses, LogoddsExample, SequenceProbExample, NumericExample, TaskType
  from .isp_utils import BasicParser
  from .isp_utils import OpenAIModel, OpenaAIModelList
label_desc: Use image node_id 1 to create a new HFModel object from inherited base classes: Model with example: obj = HFModel(model_name, device)